How Do Depression Medications Taken by Pilots Affect Passengers’ Willingness to Fly—A Mediation Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p>The mental health of airline pilots has been a concern for decades. In 2010, the United States Federal Aviation Administration began allowing four types of selective serotonin reuptake inhibitors (SSRIs) to be used by pilots suffering from depression. After a procedural wait period, pilots may be awarded a special issuance of their medical certificates to maintain flight currency. Missing from the literature was any research on consumer’s perceptions of pilots taking antidepressants, along with some other approved medications. Therefore, the purpose of the current study was to examine consumer’s willingness to fly once told that the pilot of their hypothetical flight was taking medication compared to a control group in which the pilot was not on any prescribed and approved medications. The current study also manipulated dosage levels and gathered affect data to determine if consumers’ responses were rationally or emotionally motivated. Across two studies, consumers were less willing to fly when the pilot was taking medication, and when the medication was a high dose opposed to a low dose. Additionally, affect was found to completely mediate the relationship between three of the four medications when compared to the control condition, suggesting that participants’ responses were emotionally driven. Finally, a discussion of the findings and practical implications of the study are provided.</p>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it